Senior AI/ML Scientist: GenAI & Predictive Solutions Lead

Blue Cross NC; Charleston (SC); Híbrido; USD 144.000 - 230.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Annual Incentive Bonus

401(k) with employer match

Paid Time Off

Descripción de la vacante

Blue Cross and Blue Shield of North Carolina is seeking a senior AI/ML scientist to lead the identification, research, and development of transformative GenAI solutions that translate data into actionable decisions in real-world systems.

The role combines statistical expertise, software engineering, and data science to deliver self-learning models, collaborate with multidisciplinary teams, and drive business impact across the organization.

Formación

• Bachelor's degree or advanced degree required; 5+ years in related field.
• In lieu of degree, 7+ years of related experience.

Responsabilidades

• Own delivery of ML/DL/GenAI systems with self-learning capabilities.
• Design and evaluate AI systems for production use to meet business needs.
• Apply prescriptive analytics like optimization and recommendations.
• Lead experiments, data collection, and ML performance optimization.
• Stay updated with AI advances and adapt methods to business problems.
• Benchmark methods and analyze results to identify improvements.
• Develop prototypes and PoCs to demonstrate AI feasibility.
• Lead consultations with partners to align AI approaches with business goals.
• Drive continuous improvement by trying novel techniques.
• Leverage software engineering in building sophisticated ML models.
• Communicate results to cross-functional groups to influence decisions.

Conocimientos

AI

Benchmarking

Data Analysis

Data Science

Deep Learning

Machine Learning

Reinforcement Learning

Educación

Bachelor's degree or advanced degree

Descripción del empleo

Blue Cross and Blue Shield of North Carolina is seeking a senior AI/ML scientist to lead the identification, research, and development of transformative GenAI solutions that translate data into actionable decisions in real-world systems.

The role combines statistical expertise, software engineering, and data science to deliver self-learning models, collaborate with multidisciplinary teams, and drive business impact across the organization.